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An automated quantitative image analysis tool for the identification of microtubule patterns in plants
Author(s) -
Faulkner Christine,
Zhou Ji,
Evrard Alexandre,
Bourdais Gildas,
MacLean Dan,
Häweker Heidrun,
Eckes Peter,
Robatzek Silke
Publication year - 2017
Publication title -
traffic
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.677
H-Index - 130
eISSN - 1600-0854
pISSN - 1398-9219
DOI - 10.1111/tra.12505
Subject(s) - microtubule , biology , subcellular localization , computational biology , cytoskeleton , identification (biology) , microbiology and biotechnology , confocal , biochemistry , cell , botany , cytoplasm , geometry , mathematics
High throughput confocal imaging poses challenges in the computational image analysis of complex subcellular structures such as the microtubule cytoskeleton. Here, we developed CellArchitect , an automated image analysis tool that quantifies changes to subcellular patterns illustrated by microtubule markers in plants. We screened microtubule‐targeted herbicides and demonstrate that high throughput confocal imaging with integrated image analysis by CellArchitect can distinguish effects induced by the known herbicides indaziflam and trifluralin. The same platform was used to examine 6 other compounds with herbicidal activity, and at least 3 different effects induced by these compounds were profiled. We further show that CellArchitect can detect subcellular patterns tagged by actin and endoplasmic reticulum markers. Thus, the platform developed here can be used to automate image analysis of complex subcellular patterns for purposes such as herbicide discovery and mode of action characterisation. The capacity to use this tool to quantitatively characterize cellular responses lends itself to application across many areas of biology.